Enhancing M Enhancing mathematics problem-solving skills in AI-driven environment: Integrated SEM-neural network approach

Abstract

This study explores the nexus of gamification, artificial intelligence (AI), and mathematics cognition. Sample size of 71 responded in an intervention using game-based learning (GBL) approach. The purpose of designing the GBL was to enhance computational thinking and mathematical skills. The research employed multigroup partial least squares structural equation modelling (MGA-PLS-SEM) and artificial neural networks (ANN) through multilayer perceptron (MLP) as data analysis technique. The findings showed significant positive influence on class engagement, attitudes toward mathematics, as well as student performance. The analysis also revealed gender-related variations, which affirmed the model's consistency across diverse groups. The study validated the hypothesis and consequently advocated for the transformative potential of gamification, in preparation of 21st-century learners for AI-driven digital landscape. The implications are to ensure the integration of gamified elements into educational strategies, benefiting educators, curriculum developers, and policymakers resonating strongly for educators, curriculum developers, and policymakers.